Semiconductor devices such as logic and memory devices are typically fabricated by a sequence of processing steps applied to a substrate or wafer. The various features and multiple structural levels of the semiconductor devices are formed by these processing steps. For example, lithography is a semiconductor fabrication process that involves generating a pattern on a semiconductor wafer. Additional examples of semiconductor fabrication processes include, but are not limited to, chemical-mechanical polishing (CMP), etch, deposition, and ion implantation. Multiple semiconductor devices may be fabricated on a single semiconductor wafer and then separated into individual semiconductor devices.
Inspection processes are used at various steps during a semiconductor manufacturing process to detect defects on wafers to promote higher yield. As design rules and process windows continue to shrink in size, inspection systems are required to capture a wider range of physical defects on wafer surfaces while maintaining high throughput.
Wafer manufacturing process control is typically performed based on low wafer sampling using a slow, but sensitive, inspection tool, followed by review using a scanning electron microscope (SEM). In some cases, process monitoring and control is achieved by way of a learning-based method where a process engineer learns how long the process tool can be used before requiring maintenance. This process engineer-based approach is prone to random failures since there is no in-line feedback. In both of these previous techniques, issues are only detected once a process tool has become problematic and creates defects that can be observed on inspection. Additionally, these techniques are slow, and therefore, wafer sampling is low.
Previous high-throughput approaches lack sensitivity and versatility. For example, previous techniques may detect known patterns in pre-defined zones on a wafer.
Accordingly, there is a need for high-throughput process monitoring and control that is capable of detecting non-compliance based on previously unknown patterns.